M.T. Brunetti, M. Melillo, S.L. Gariano, L. Ciabatta, L. Brocca, Giriraj Amarnath, S. Peruccacci, 2022, Performance of satellite rainfall products for landslide prediction in India, European Geophysical Union (EGU) 2022, Vienna, 23-27/05/2022,
URL: http://www.cnr.it/prodotto/i/463181

Landslides are among the most dangerous natural hazards, especially in developing countries. In these areas, where rain gauge networks are scarce, satellite rainfall products can be a viable alternative for landslide prediction. To date, only a few studies have investigated the capability and effectiveness of these products in regional-scale landslide prediction. We performed a comparative study on the reliability of ground-based rainfall products and satellite rainfall products for landslide prediction in India. We used a catalog of 197 rainfall-induced landslides over the 13-year period between April 2007 and October 2019. We calculated frequentist rainfall thresholds using GPM, SM2RAIN-ASCAT satellite products, and their merging, at daily and hourly temporal resolution, and ground-based data from the rainfall network of the Indian Meteorological Department (IMD) at daily resolution. The results indicate that satellite rainfall products outperform ground-based observations in the prediction of landslides due to their improved spatial (0.1° vs. 0.25°/pixel) and temporal (hourly vs. daily) resolutions. The best performance is achieved through the merging of GPM and SM2RAIN-ASCAT. These results open up the possibility for using satellite rainfall products in landslide early warning systems, particularly in poorly gauged areas.

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